Data Science Master |
Core Courses |
Data Analysis |
Information and Learning |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
252-0535-00L | Advanced Machine Learning | W | 8 credits | 3V + 2U + 2A | |
252-0535-00 V | Advanced Machine Learning
Vorlesung: Donnerstag im ML D 28 mit Videoübertragung im ML E 12 Freitag im HG F 1 mit Videoübertragung im HG F 3 | | | 3 hrs | | J. M. Buhmann |
252-0535-00 U | Advanced Machine Learning | | | 2 hrs | | J. M. Buhmann |
252-0535-00 A | Advanced Machine Learning
Project Work, no fixed presence required. | | | 2 hrs | | J. M. Buhmann |
227-0423-00L | Neural Network Theory | W | 4 credits | 2V + 1U | |
227-0423-00 V | Neural Network Theory | | | 2 hrs | | H. Bölcskei,
E. Riegler |
227-0423-00 U | Neural Network Theory | | | 1 hrs | | H. Bölcskei,
E. Riegler |
|
Statistics |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
401-3621-00L | Fundamentals of Mathematical Statistics | W | 10 credits | 4V + 1U | |
401-3621-00 V | Fundamentals of Mathematical Statistics | | | 4 hrs | | S. van de Geer |
401-3621-00 U | Fundamentals of Mathematical Statistics | | | 1 hrs | | S. van de Geer |
|
Data Management |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
263-3010-00L | Big Data | W | 8 credits | 3V + 2U + 2A | |
263-3010-00 V | Big Data | | | 3 hrs | | G. Fourny |
263-3010-00 U | Big Data
Groups are selected in myStudies.
| | | 2 hrs | | G. Fourny |
263-3010-00 A | Big Data
Individual work to get hands-on experience with the technologies covered, no fixed presence required. | | | 2 hrs | | G. Fourny |
263-4500-10L | Advanced Algorithms (with Project) Only for Data Science MSc. | W | 8 credits | 2V + 2U + 2P + 1A | |
263-4500-00 V | Advanced Algorithms | | | 2 hrs | | M. Ghaffari,
A. Krause |
263-4500-00 U | Advanced Algorithms | | | 2 hrs | | M. Ghaffari,
A. Krause |
263-4500-10 P | Advanced Algorithms | | | 2 hrs | | A. Krause |
263-4500-00 A | Advanced Algorithms | | | 1 hrs | | M. Ghaffari,
A. Krause |
|
Core Electives |
Number | Title | Type | ECTS | Hours | Lecturers |
---|
151-0563-01L | Dynamic Programming and Optimal Control | W | 4 credits | 2V + 1U | |
151-0563-01 V | Dynamic Programming and Optimal Control
The lecture will start in the 2nd week of Semester. | | | 2 hrs | | R. D'Andrea |
151-0563-01 U | Dynamic Programming and Optimal Control
The exercise will start in the 2nd week of Semester. | | | 1 hrs | | R. D'Andrea |
227-0101-00L | Discrete-Time and Statistical Signal Processing | W | 6 credits | 4G | |
227-0101-00 G | Discrete-Time and Statistical Signal Processing | | | 4 hrs | | H.‑A. Loeliger |
227-0417-00L | Information Theory I | W | 6 credits | 4G | |
227-0417-00 G | Information Theory I | | | 4 hrs | | A. Lapidoth |
227-0427-00L | Signal Analysis, Models, and Machine Learning | W | 6 credits | 4G | |
227-0427-00 G | Signal Analysis, Models, and Machine Learning | | | 4 hrs | | H.‑A. Loeliger |
227-0689-00L | System Identification | W | 4 credits | 2V + 1U | |
227-0689-00 V | System Identification | | | 2 hrs | | R. Smith |
227-0689-00 U | System Identification | | | 1 hrs | | R. Smith |
252-0417-00L | Randomized Algorithms and Probabilistic Methods | W | 8 credits | 3V + 2U + 2A | |
252-0417-00 V | Randomized Algorithms and Probabilistic Methods | | | 3 hrs | | A. Steger |
252-0417-00 U | Randomized Algorithms and Probabilistic Methods | | | 2 hrs | | A. Steger |
252-0417-00 A | Randomized Algorithms and Probabilistic Methods
Project Work, no fixed presence required. | | | 2 hrs | | A. Steger |
252-1407-00L | Algorithmic Game Theory | W | 7 credits | 3V + 2U + 1A | |
252-1407-00 V | Algorithmic Game Theory | | | 3 hrs | | P. Penna |
252-1407-00 U | Algorithmic Game Theory | | | 2 hrs | | P. Penna |
252-1407-00 A | Algorithmic Game Theory
Project Work, no fixed presence required. | | | 1 hrs | | P. Penna |
252-1414-00L | System Security | W | 7 credits | 2V + 2U + 2A | |
252-1414-00 V | System Security | | | 2 hrs | | S. Capkun,
A. Perrig |
252-1414-00 U | System Security
The exercises begin in the second week of the semester. | | | 2 hrs | | S. Capkun,
A. Perrig |
252-1414-00 A | System Security | | | 2 hrs | | S. Capkun,
A. Perrig |
261-5130-00L | Research in Data Science Only for Data Science MSc. | W | 6 credits | 13A | |
261-5130-00 A | Research in Data Science | | | 180s hrs | | Professors |
263-0006-00L | Algorithms Lab Only for master students, otherwise a special permission by the student administration of D-INFK is required. | W | 8 credits | 4P + 3A | |
263-0006-00 P | Algorithms Lab | | | 4 hrs | | A. Steger |
263-0006-00 A | Algorithms Lab
Project Work, no fixed presence required. | | | 3 hrs | | A. Steger |
263-0007-00L | Advanced Systems Lab Limited number of participants. Takes place the last time in this form. Students who repeat the lab have priority. All others have to take the course in the spring semester 20! | W | 8 credits | 4P + 3A | |
263-0007-00 P | Advanced Systems Lab
 | | | 4 hrs | | G. Alonso |
263-0007-00 A | Advanced Systems Lab
Project Work, no fixed presence required. | | | 3 hrs | | G. Alonso |
263-2400-00L | Reliable and Interpretable Artificial Intelligence | W | 5 credits | 2V + 1U + 1A | |
263-2400-00 V | Reliable and Interpretable Artificial Intelligence | | | 2 hrs | | M. Vechev |
263-2400-00 U | Reliable and Interpretable Artificial Intelligence
No exercise session in the first semester week. Exercise session will start in the second week of the semester. | | | 1 hrs | | M. Vechev |
263-2400-00 A | Reliable and Interpretable Artificial Intelligence | | | 1 hrs | | M. Vechev |
263-2800-00L | Design of Parallel and High-Performance Computing | W | 8 credits | 3V + 2U + 2A | |
263-2800-00 V | Design of Parallel and High-Performance Computing | | | 3 hrs | | M. Püschel,
T. Ben Nun |
263-2800-00 U | Design of Parallel and High-Performance Computing | | | 2 hrs | | M. Püschel,
T. Ben Nun |
263-2800-00 A | Design of Parallel and High-Performance Computing
Project Work, no fixed presence required. | | | 2 hrs | | M. Püschel,
T. Ben Nun |
263-3210-00L | Deep Learning | W | 5 credits | 2V + 1U + 1A | |
263-3210-00 V | Deep Learning
Vorlesung im HG F7 mit Videoübertragung im HG F5. | | | 2 hrs | | T. Hofmann |
263-3210-00 U | Deep Learning | | | 1 hrs | | T. Hofmann |
263-3210-00 A | Deep Learning | | | 1 hrs | | T. Hofmann |
263-5210-00L | Probabilistic Artificial Intelligence | W | 5 credits | 2V + 1U + 1A | |
263-5210-00 V | Probabilistic Artificial Intelligence
Vorlesung im HG E 7 mit Videoübertragung im HG E 3. | | | 2 hrs | | A. Krause |
263-5210-00 U | Probabilistic Artificial Intelligence | | | 1 hrs | | A. Krause |
263-5210-00 A | Probabilistic Artificial Intelligence | | | 1 hrs | | A. Krause |